Artificial Neural Network Application to Load Forecasting in a Large Hospital Facility

被引:0
作者
Bagnasco, A. [1 ]
Saviozzi, M. [1 ]
Silvestro, F. [1 ]
Vinci, A. [1 ]
Grillo, S. [2 ]
Zennaro, E. [3 ]
机构
[1] Univ Genoa, DITEN IEES Lab, Genoa, Italy
[2] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, Milan, Italy
[3] Univ Roma La Sapienza, Dept Elect Engn, Rome, Italy
来源
2014 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS) | 2014年
关键词
Load forecasting; artificial neural network; distributed generation; smart grids;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
A Smart Grid approach to electric distribution system management needs to front uncertainties in generation and demand thus making forecasting an up-to-date area of research in electric energy systems. This works aims to propose a day-ahead load forecasting procedure for a medium voltage customer. The load forecasting is performed through the implementation of an artificial neural network (ANN). The proposed multi-layer perceptron ANN, based on backpropagation training algorithm, is able to take as inputs: loads, data concerning the type of day (e.g. weekday/holiday), time of the day and weather data (e.g. temperature, humidity). This procedure has been tested to predict the loads of a large university hospital facility located in Rome.
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页数:6
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